1. Technical Field
The present teaching relates to system and method for medical image processing and diagnosis. Particularly, the present teaching relates to system and method for interactive 3D medical image processing and diagnosis and systems incorporating the same.
2. Discussion of Related Art
In liver transplant or liver resection practices, an accurate liver division or liver lobe separation is crucial. Since each lobe is a self-contained unit which has its own vascular inflow, outflow, and biliary drainage, each lobe can be resected without damaging other parts of the liver. For example, according to the Couinaud classification, a liver can be subdivided up to 8 independent lobes (identified as Roman numerals I to VIII). However, in some practices, fewer numbers of subdivisions may suffice. For example, when a lesion occurs within a lateral segment of the left lobe, both Couinaud lobes II and III are usually removed based on the plane formed by the umbilical fissure (left lateral segmentectomy). Therefore, the number of divisions and ways of dividing a liver into such segments can be determined based on different application scenarios.
An effective tool that can offer the flexibility to enable a user to make different types of separation and/or perform needed surgical planning is of a great help. With advancement of technologies, images from various medical scanners are frequently post-processed by computer-aided software. A reconstructed 3D volume can be obtained by stacking a series of 2D images together. An internal organ such as a liver can be segmented either automatically via intelligent medical image processing software or by a human based on interactive segmentation tools. However, there are needs to further segment such a 3D volume into sub-parts. For example, a liver may include a plurality of lobes and there are situations in which individual lobes have to be separately identified. Systems or software that are currently offered in the market place provide only rather primitive tools to allow a user to manipulate a segmented 3D object such as a liver. They are usually 2D based and separating a 3D object into sub-parts has to be done based on 2D slices in a 2D data manipulation environment. It is very difficult to achieve the separation due to the fact that some of the landmarks or features in such a 3D object may be 3D in nature and it is often hard to visualize based on 2D slice images. It is also very time consuming and, thus, inefficient because users have to go through hundreds of slices one at a time.